Principal Machine Learning Systems Engineer (GenAI Products & Knowledge Innovations)

Atlassian; Washington, Northern (District of Columbia, KY); Hybrid; USD 237,000 - 309,000; Full time

Benefits offered by this job

Bonuses

Equity

Commissions

Health benefits

Job summary

At Atlassian, we’re advancing Generative AI to empower teams worldwide. We seek a Principal ML Systems Engineer to design and scale GenAI systems, tackle training, inference, and knowledge-grounded pipelines, and partner with cross‑functional teams to ship production‑ready innovations.

You will influence architecture, optimize performance, and help establish best practices for deployment, monitoring, and evaluation across cloud environments and modern containerized infrastructure.

Qualifications

• 6+ years in ML systems engineering or related roles.
• Proven ability to scale ML-powered services in production.
• Experience with large-scale training and inference pipelines.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Experience with vector databases and orchestration tools.
• Strong coding skills and performance-focused mindset.
• Familiarity with AWS, GCP, and Azure cloud environments.

Responsibilities

• Design and build scalable ML systems for training, fine-tuning, and serving LLMs.
• Develop retrieval, hybrid search, and RAG pipelines with knowledge grounding.
• Create tools and infra for rapid experimentation and deployment.
• Partner with scientists to productionize prototypes.
• Evolve POC systems into reliable services.
• Optimize latency, throughput, and resource use for GenAI workloads.
• Collaborate with ML engineers, backend teams and product to ship end-to-end innovations.
• Establish model deployment, monitoring, and evaluation best practices.
• Position Atlassian as a hub for GenAI systems innovation.

Skills

ML systems engineering

Backend engineering

Model training

Python

PyTorch

TensorFlow

Hugging Face

Weaviate

Pinecone

FAISS

LangChain

LlamaIndex

AWS

GCP

Azure

Kubernetes

Docker

Education

Bachelor’s or Master’s in Computer Science, ML, or related field

Tools

PyTorch

TensorFlow

Hugging Face

Weaviate

Pinecone

FAISS

LangChain

LlamaIndex

Kubernetes

Docker

Job description

Principal Machine Learning Systems Engineer (GenAI Products & Knowledge Innovations)

Engineering | Washington DC, United States | Remote, Remote | Mountain View, United States or Remote | San Francisco, United States |

At Atlassian, we’re on a mission to unleash the potential of every team. As part of that mission, we're investing deeply in Generative AI — pioneering advanced modeling and rapid innovations that accelerate how teams work, discover, and create.

We’re seeking a Principal Machine Learning Systems Engineer (P60) to lead technical directions of GenAI Products & Knowledge Innovations in US. You’ll focus on building and scaling the systems that power advanced GenAI products with enterprise knowledge, rapid prototyping, and applied research—bridging cutting‑edge algorithms with reliable, high-performance infrastructure.

Working at Atlassian

Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.

What You’ll Do

Design and Build ML Systems

Architect and implement scalable systems for training, fine‑tuning, and serving large language models and embeddings.

Build efficient retrieval, hybrid search, and RAG pipelines integrated with knowledge‑grounded data.

Develop tools and infra to support rapid experimentation, evaluation, and deployment of prototypes.

Partner with applied scientists to bring new ideas to life in robust, production‑ready pipelines.

Build proof‑of‑concept (POC) systems and evolve them into reliable, scalable services.

Optimize latency, throughput, and resource efficiency for GenAI workloads.

Work closely with ML engineers, backend developers, and product teams to ship end‑to‑end innovations.

Contribute to best practices in model deployment, monitoring, and evaluation.

Help establish the team as a world‑class hub for GenAI systems innovation.

At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.

Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.

This role may also be eligible for benefits, bonuses, commissions, and equity.

In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:

Zone A: $236,700 - $309,025

Zone B: $213,030 - $278,123

Zone C: $196,461 - $256,491

What We’re Looking For

6+ years in ML systems engineering, backend engineering, or infrastructure roles.

Strong track record of building and scaling ML‑powered services in production.

Experience with large‑scale model training, inference pipelines, or search/retrieval systems.

Proficiency in backend systems and ML frameworks (Python, PyTorch, TensorFlow, Hugging Face).

Experience with vector databases (Weaviate, Pinecone, FAISS), orchestration frameworks (LangChain, LlamaIndex).

Strong coding skills and ability to optimize systems for performance and reliability.

Familiarity with cloud environments (AWS, GCP, Azure) and container/orchestration tools (Kubernetes, Docker).

Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent industry experience.

Nice to Have

Background in distributed systems, high‑performance computing, or GPU optimization.

Familiarity with search/GenAI evaluation metrics (e.g., NDCG, groundedness, latency benchmarks).

Experience with monitoring, observability, and reliability practices for ML systems.

Contributions to open‑source infra or ML systems frameworks.

Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits .

About Atlassian

At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.

We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.